BibTeX

Years of Citing Articles

Bookmark

OpenURL

Abstract

Sentence alignment is a task that requires not only accuracy, as possible errors can affect further processing, but also requires small computation resources and to be language pair independent. Although many implementations do not use translation equivalents because they are dependent on the language pair, this feature is a requirement for the accuracy increase. The paper presents a hybrid sentence aligner that has two alignment iterations. The first iteration is based mostly on sentences length, and the second is based on a translation equivalents table estimated from the results of the first iteration. The aligner uses a Support Vector Machine classifier to discriminate between positive and negative examples of sentence pairs. 1.

Citations

... pairs, when characterized only by this feature, can be classified as “good” or “bad” with an accuracy of 98.47%. For the estimation of the translation equivalence, we use the well-known IBM model 1 (=-=Brown et al. 1993-=-). In the estimation, besides translation equivalence, we also use features dependent of the context of the alignment (Tufis et al. 2005a, b). The link locality feature accounts for the degree of the ...